PSC 290 - Data Visualization
The Spike-and-Slab Mixed-Effects Location Scale model (SS-MELSM) methodology identifies clustering units (students, classrooms, etc.) that exhibit unusual levels of residual variability—such as consistency or inconsistency—in academic achievement.
The Posterior Inclusion Probability (PIP), quantifies the probability that a given random effect is included in the residual variance (scale) model.
Evidence for retaining the random effect is evidence of unusual variability.
ivd is a package that facilitates the implementation of the SS-MELSM.
Once (in)consistent schools are identified, researchers may want to investigate these clusters to understand what distinguishes them from others.
How can we visualize these clusters to clearly highlight what makes them unique compared to others?
ivd package.Standardized math scores from 11,386 11th and 12th-grade students across 160 schools.
I will work with posterior estimates from the scale model.
Specifically, I will use the PIPs, the estimated random effects standard deviations, the within-school residual variance, and the estimated math scores.